Heightened consumer demand for highly reliable goods and services has made quality an increasingly important issue for businesses. This ever-growing consumer demand for quality has lead to an increased emphasis placed on quality control and improvement at virtually all levels of business operations, including engineering, manufacturing, distribution, and other administrative operations. Over the years, various quality analysis tools and computer programs have been developed in an attempt to aid businesses analyze and improve the quality of their processes and products. Such conventional tools and computer programs, however, suffer from a number of drawbacks and deficiencies.
For example, while many conventional quality analysis computer programs are capable of performing various statistical tasks and experiments that, when performed correctly, may help businesses identify ways to improve the quality of their products and processes, the user interface employed in such programs is typically designed for use by highly skilled statisticians. In particular, the terminology used, the user input required to design tests and experiments, and the manner in which the results of such experiments are displayed in conventional quality analysis programs typically require specialized training and expertise in the field of statistics for sufficient operation and comprehension of the same. As a result, business owners, management personnel, and other decision makers having minimal experience in statistics generally find the use and application of such programs intimidating, problematic, and unproductive.
Accordingly, there exists a need for a system, method and program capable of maximizing the functionality and success of process improvement projects, while minimizing the effort and complexity presented to the user. More particularly, there exists a need for a simplified user interface for a quality analysis computer program capable of enabling persons with only minimal training in statistics to simply, efficiently and effectively analyze and improve processes.